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Believing the Machine: Human Trust and the Impact of AI Language Confidence and Elaboration
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An AI research paper on Believing the Machine: Human Trust and the Impact of AI Language Confidence and Elaboration.
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Chinese explanation / 中文解读
中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。
Original abstract
As artificial intelligence increasingly acts as a cognitive partner in decision-making, understanding how users evaluate and trust AI recommendations is critical. While prior research emphasizes algorithmic accuracy, less attention has been given to how presentation features, particularly linguistic confidence and elaboration, shape trust independent of correctness. This study examines how these cues influence trust, attention, and emotional engagement during AI-assisted decisions. Drawing on persuasion theory, trust in automation, and the Elaboration Likelihood Model, it proposes three within-subject experiments using ChatGPT-style outputs. Experiment 1 manipulates confidence framing and format, Experiment 2 varies elaboration depth and format, and Experiment 3 examines accuracy with confidence. Multimodal biometrics capture real-time responses alongside survey-based trust measures.
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